Abstract
The library data management system of academic institutions generates and stores data with information on lends, returns and queries made by users daily. This research aims to provide a useful method to transform this data to obtain relevant knowledge for the management of the library. The process used consisted of a data pre-processing, data transformation and cleaning, and finally the use of privacy and association algorithms. We clarify the proposed method for a university library in Peru where significant results were obtained in the form of association rules. This shows that it is a efficient alternative to have a more detailed knowledge to make better decisions.
| Original language | English |
|---|---|
| Title of host publication | Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings |
| Editors | Juan Antonio Lossio-Ventura, Denisse Muñante, Hugo Alatrista-Salas |
| Publisher | Springer Verlag |
| Pages | 112-120 |
| Number of pages | 9 |
| ISBN (Print) | 9783030116798 |
| DOIs | |
| State | Published - 2019 |
| Externally published | Yes |
| Event | 5th International Conference on Information Management and Big Data, SIMBig 2018 - Lima, Peru Duration: 3 Sep 2018 → 5 Sep 2018 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 898 |
| ISSN (Print) | 1865-0929 |
Conference
| Conference | 5th International Conference on Information Management and Big Data, SIMBig 2018 |
|---|---|
| Country/Territory | Peru |
| City | Lima |
| Period | 3/09/18 → 5/09/18 |
Bibliographical note
Publisher Copyright:© 2019, Springer Nature Switzerland AG.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 17 Partnerships for the Goals
Keywords
- Association rules
- Knowledge data discovery
- Library management
- Pre-processing
- Privacy
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